Brain monitoring system

ABSTRACT

Systems and methods capture light reflected back from a patient&#39;s fundus and compares the resulting images to prior images, to determine if the patient is experiencing intraocular inflammation or atrophy.

This application is a divisional application of U.S. application Ser.No. 15/971,740, filed May 4, 2018, now U.S. Pat. No. 10,849,547, whichclaims priority to U.S. Provisional Application No. 62/501,482 filed 4May 2017, each of which is hereby incorporated by reference in itsentirety.

BACKGROUND Field of Endeavor

This application's subject matters relate to systems and methods formonitoring brain and retina function of a patient.

Brief Description of the Related Art

Inflammation is a hallmark of eye and brain damage and is implicated insuch common retinal diseases as age-related macular degeneration (AMD)and glaucoma, as well as a range of brain ailments from multiplesclerosis (MS) to traumatic brain injury (TBI). Studies have furtherestablished a relationship between inflammation in the retina and braindisease progress, such that worsening of neuroinflammation oftenprecedes the onset of patient symptoms. These include an associationbetween increased retinal layer thickness (possibly representinginflammation) and MS disease activity [1], the detection of a corticalimmune response in the retina following an epileptic seizure [2], andincreased inflammation in the retinas of rats with repetitive mildtraumatic brain injuries (mTBI) [3]. Evidence from MS studies alsosuggests that inflammatory processes in specific retinal layers mayinform specific cortical disease processes [1]. However, gold standardapproaches for monitoring these conditions are often invasive,expensive, and limited to specialized healthcare facilities.

Given the impact of inflammation on brain and ocular function andpatient prognosis, a critical need exists for a device that enablespatients with neuroinflammatory conditions to measure changes in theirretinal pathology at home, thus allowing their physicians to objectivelyand more frequently monitor patients' disease activity remotely. Fundusautofluorescence (FAF) and optical coherence tomography (OCT) are bothnon-invasive retinal imaging modalities that can be used for thispurpose.

Fundus autofluorescence (FAF) is a safe, non-invasive modality that usesfundus photography to identify regions of the retina with increasedaccumulation of lipofuscin—a natural fluorophore located in neurons ofthe retina and cortex. Lipofuscin accumulation (presenting as increasedautofluorescence) is indicative of activated microglia activity [4],where structures containing lipofuscin (such as the retina's RPE layer)are phagocytized and released or accumulated in macrophages. Thisincreased accumulation is thus a sign of degeneration, inflammation,infection, and/or toxicity.

Autofluorescence occurs when fluorophores absorb and then emit aspecific wavelength of light. Traditional FAF uses a blue light (˜470nm) to excite lipofuscin in the retina, and collects the resultingemissions using a filter and detector that are preset to the relevantspectra (600-610 nm). A brightness map can then be created thatillustrates the distribution and density of lipofuscin across the retinaand thus pinpoint areas that are abnormal.

Optical coherence tomography (OCT) is similarly a widely-used,non-invasive modality for imaging the retina. While FAF focuses onfunctional mapping of the retina, OCT provides structural images of theretinal surface and layers. The technique is based on low-coherenceinterferometry, in which reflected light from a reference arm (i.e.,mirror) and sample are combined to create an interference pattern. Whenthe reference mirror is scanned (e.g., using a micro-electro-mechanicalsystem [MEMS] scanner), interference patterns across the sample can begenerated, resulting in a series of axial depth scans (A-scans).Multiple A-scans over a transverse line can then be combined to createcross-sectional (B-scan) structural images of the sample. Whiletime-domain OCT (TD-OCT) uses a scanning reference mirror, swept-sourceFourier-domain OCT (SS FD-OCT) uses a tunable laser that quickly sweepsthrough a narrow band of wavelengths to acquire A-scan images (thereference mirror remains fixed).

In the case of the retina, OCT images can indicate changes in thethickness of specific retinal layers due to atrophy or inflammation.Studies have further identified a correlation between OCT and FAFmeasures in retinal diseases, where changes in autofluorescence wereassociated with (and may serve as a predictor of) the progression ofgeographic atrophy or inflammation [5,6].

Currently available systems for combination OCT and FAF imaging by eyecare professionals include Zeiss' CIRRUS Photo 80028 [7], HeidelbergEngineering's Spectralis Diagnostic Imaging Platform [8], and Topcon's3D OCT-2000 FA plus [9]. A new portable OCT space is also gainingtraction that includes several marketed products. Handheld OCT andfundus devices are designed for use by healthcare providers forscreening and evaluation of retinal diseases in non-traditionalsettings, including the D-EYE Portable Retinal Imaging System [10], VolkPictor Plus handheld fundus camera [11], Zeiss' Visuscout 100 handheldfundus camera [12], Jedmed's Horus Scope handheld fundus camera [13],and Envisu C2300 handheld OCT system from Leica Microsystems (atechnology acquired from their acquisition of Bioptigen, Inc.) [14].Though not handheld, Optovue's iVue and iFusion comprise a portable OCTand fundus camera combination system currently on the market [15].

Several other portable technologies have been developed by researchgroups but do not have FDA approval, including portable OCT systems foruse during surgery and on infants and children in the clinical setting.A tabletop Spectralis OCT system was modified into a handheld unit byVinekar et al. and used to image retinal pathology in infants [16],while two groups integrated OCT into a microscope for interoperative use[17,18]. Lu et al. further developed an ultrahigh speed, handheld OCTinstrument using a MEMS scanning mirror [19]. Development of a low-cost,portable OCT system was recently demonstrated by Kim et al. [20].

SUMMARY

While the devices described above can be used to measure retinalpathology, the subject matter described in this application includes atleast the following differences, which can be key in certainapplications:

1. It is specifically designed for patient use at home, includingruggedization of the system components for durability under a range oftemperatures, pressures, humidity, shock, and accelerations.

2. It can include a modular design—including a headset unit—that allowsthe imaging interface to be attached directly to the patient,significantly reducing motion artifacts and the need for re-imaging. Theheadset has a lightweight, ergonomic design and includes a blackoutcomponent that allows a user's eye to naturally dilate after donning theheadset, for non-mydriatic OCT and FAF imaging.

3. In one exemplary design, it utilizes a motorized flip mirror thatdirects a beam of light to and from the user's right or left eye of theheadset for sequential imaging of each eye.

4. In one exemplary design, double-cladding fiber can be used toimplement an all-fiber OCT/FAF system to achieve simultaneous OCT andFAF image acquisition.

5. It can include automated image acquisition, processing, analysis, andtransmission of results from the device to a clinician in aHIPPA-compliant manner for remote assessment of retinal pathology. Datacan advantageously be stored on a cloud server.

6. It can include image processing software to automatically makespecific adjustments that compensate for the distance between a user'seyes, pupil size, light levels, etc.

7. It can include voice commands to guide the user through the imageacquisition process.

8. It can include a mobile software application that presents changes inresults over time to the user and/or a clinician for regular monitoringof disease activity.

9. It can use a combined FAF and OCT image analysis routine to trackactive changes in inflammatory activity within specific retinal layers;FAF can detect functional changes in retinal inflammation that occurbefore a structural change can be identified with OCT, leading toearlier detection of retinal pathology changes.

According to a first aspect of the invention, a system useful for FAFand OCT image acquisition of a patient's eye comprises a broadband LEDas an FAF light source, a tunable laser as an OCT light source, acoupler, a first lightpath communicating visible light from thebroadband LED, the first lightpath including an excitation filter, thefirst lightpath communicating light from the excitation filter to thecoupler, a second lightpath communicating near infrared light from saidtunable laser to said coupler, wherein the coupler combines light fromsaid first and second lightpaths, a single-mode fiber receiving lightfrom said coupler, a splitter receiving light form said single-modefiber, third and fourth lightpaths receiving light from said splitter, areference arm in said third lightpath, and a headset sample arm in saidfourth lightpath.

According to another aspect of the present invention, an imageacquisition headset comprises at least one goggle configured to fit overa portion of a patient's face and cover at least one eye, a strapattached to the at least one goggle for securing said at least onegoggle to the patient's head, an image data acquisition modulecomprising a lightpath having a broadband light source, a firstaperture, a lens system including a first beam splitter, an autofocuslens, a secondary aperture, second beam splitter, a camera, and a signalprocessing unit in electrical communication with said camera.

According to yet another aspect of the present invention, a process ofFAF and OCT image acquisition of a patient's eye comprises generatinglight with a broadband LED and tunable laser, wherein visible light fromthe broadband LED first travels through a lipofuscin excitation filter,combining light from said excitation filter with near infrared lightfrom said tunable laser, splitting and transmitting light from saidcombining step to a reference arm, and a headset sample arm configuredto be positioned in front of a patient's eye.

Still other aspects, features, and attendant advantages of the presentinvention will become apparent to those skilled in the art from areading of the following detailed description of embodiments constructedin accordance therewith, taken in conjunction with the accompanyingdrawings.

BRIEF DESCRIPTION OF THE DRAWINGS

The invention of the present application will now be described in moredetail with reference to exemplary embodiments of the apparatus andmethod, given only by way of example, and with reference to theaccompanying drawings, in which:

FIG. 1A illustrates the headset-only version of a system embodyingprinciples of the present disclosure.

FIG. 1B illustrates a patient mobile app according to an exemplaryembodiment of the disclosure.

FIG. 1C illustrates a patient wearing the headset-only version of thesystem of FIG. 1A.

FIG. 2 illustrates manual vs. automatic image acquisition processes.

FIG. 3A illustrates a headset of the system of FIG. 1A configured foruse of a virtual reality function.

FIG. 3B illustrates a workflow for use of a virtual reality function toengage the user during image acquisition.

FIG. 4 Illustrates data storage and transmission among devices.

FIG. 5 summarizes steps included during image acquisition and pre- andpost-processing of the image data.

FIG. 6 illustrates an example flowchart for analysis of the FAF and OCTimage data.

FIG. 7 illustrates the clinician mobile software application.

FIG. 8 illustrates a schematic view of imaging components for theheadset-only, FAF-only version of an exemplary device.

FIG. 9A illustrates a perspective view of imaging components for theheadset-only, FAF-only version of an exemplary device.

FIG. 9B illustrates a perspective view of the imaging components of FIG.9A in a headset according to the disclosure.

FIG. 10 illustrates a 2D schematic of imaging components for theheadset-only, FAF/TD-OCT version of an exemplary device.

FIG. 11 illustrates a 2D schematic of imaging components for theheadset-only, FAF/SS-OCT version of an exemplary device.

FIG. 12 illustrates a 2D schematic of imaging components for the headsetand tabletop SS-OCT-only version of an exemplary device.

FIG. 13 illustrates a 2D schematic of imaging components for the headsetand tabletop FAF/SS-OCT version of an exemplary device.

FIG. 14 Illustrates an example workflow for the invention, includingdata acquisition by the patient, analysis, and transfer to a clinician.

FIGS. 15A, 15B, and 15C Illustrate three additional configurations ofthe headset, in which only a single imaging element is used.

DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS

Referring to the drawing figures, like reference numerals designateidentical or corresponding elements throughout the several figures.

The singular forms “a,” “an,” and “the” include plural referents unlessthe context clearly dictates otherwise. Thus, for example, reference to“a solvent” includes reference to one or more of such solvents, andreference to “the dispersant” includes reference to one or more of suchdispersants.

Concentrations, amounts, and other numerical data may be presentedherein in a range format. It is to be understood that such range formatis used merely for convenience and brevity and should be interpretedflexibly to include not only the numerical values explicitly recited asthe limits of the range, but also to include all the individualnumerical values or sub-ranges encompassed within that range as if eachnumerical value and sub-range is explicitly recited.

For example, a range of 1 to 5 should be interpreted to include not onlythe explicitly recited limits of 1 and 5, but also to include individualvalues such as 2, 2.7, 3.6, 4.2, and sub-ranges such as 1-2.5, 1.8-3.2,2.6-4.9, etc. This interpretation should apply regardless of the breadthof the range or the characteristic being described, and also applies toopen-ended ranges reciting only one end point, such as “greater than25,” or “less than 10.”

Generally, the devices and systems described herein, are wearable,non-invasive, and non-mydriatic systems that image the user's retina anduse FAF, OCT, or FAF and OCT to measure and/or identify layer-specificretinal pathology (e.g., retinal inflammation and degeneration) to helptrack the progression of eye and brain health. While OCT and FAF havebeen modalities for imaging the retina, they have not yet been madeavailable for disease monitoring at home. The systems and methodsdescribed herein are significantly different from commercially availableretinal imaging systems in that they are 1) designed specifically topermit an individual to use at home, 2) include automated imageacquisition for ease of use by the user, and 3) transmit image dataresults to a clinician in a secure (e.g., U.S.'s HIPPA laws andregulations) and compliant manner for regular, remote assessment ofdisease activity in their patients.

Several exemplary embodiments of the invention are depicted in thefigures and described below.

Overall Device Use

FIG. 1 illustrates a headset-only version of a system embodyingprinciples of the present invention, including: A) headset device, B)patient mobile software user interface showing a graphical illustrationof changes in FAF/OCT measures over time (including bottom buttons for auser dashboard [left], window to input changes in symptoms [left center]and medications [right center], and a community discussion board[right]) (10), and C) illustration of a user wearing the system andholding a mobile device that includes the software shown in B.

In this exemplary embodiment, the headset (1) is lightweight, ergonomic,and designed to be worn over the user's eyes with scanning hardware toimage each eye (see FIGS. 1 and 14). It includes adjustable straps (2),a USB port for battery charging (3), a blackout component that allowsusers' eyes to naturally dilate after donning the headset (that is, the‘lens’ of the goggle is entirely opaque, and the goggle conforms to thewearer's face and forehead so that little or no ambient light enters thegoggles when worn) (4), On/Off power button (5), “Acquire Image” buttonfor signaling to the control system to initiate manual image acquisition(6), button to signal to the control system to toggle between “Manual”and “Automatic” image acquisition modes (7), a fixation target (e.g.,red light) for user fixation during image acquisition (8), and lensopening for each eye that allows images to be acquired of each (9). Theheadset is durable (e.g., according to the U.S.'s MIL-STD-810 standardsfor ruggedization under various temperature, shock, humidity, pressure,and acceleration conditions) and may include different color and texturestraps for aesthetics and user personalization. Buttons (5-7), toactivate the system, will be easily distinguished by touch.

Image Acquisition Process

FIG. 2 illustrates the steps a user will follow to use the device ineither manual (A) or automatic (B) image acquisition modes. Users willuse the system by wearing the device's headset briefly on a regularbasis (e.g., daily, weekly, or bi-weekly). After turning the system onand donning the headset, if manual mode is chosen using the mode button,the user will hear an audible 10 second (for example) countdown from“ten” to “one” (which provides time for the user's eye to naturallydilate in darkness; this voice instruction may come from the device,mobile software application, or the like), after which a fixation target(e.g., red light) will turn on in the headset. The user-after they areready and steadily fixated on the red light—will then press the “AcquireImage” button to signal to the control system to initiate the imageacquisition process, during which time fundus, OCT, and/or FAF imageswill be acquired sequentially or simultaneously from each eye. Thesystem automatically makes specific adjustments to compensate for thedistance between the user's eyes, pupil size, light levels, etc.

After turning the system on and donning the headset, if automatic modeis chosen using the mode button, the user will hear an audible 10 second(for example) countdown from “ten” to “one”. A fixation target will thenturn on in the headset and an eye tracking algorithm will be used todetect the user's pupil and determine when the user's gaze is fixated(where, for example, fixation is defined as a gaze remaining within adiameter of 1° visual angle for at least 100 ms). After fixation isdetected, the device will automatically initiate the image acquisitionprocess.

In both manual and automatic modes, voice commands will guide thepatient through the image acquisition process. This will include thedevice informing the user if an image set was successfully acquired, orif re-imaging is required (as determined by the level of eye movementdetected during pre-processing, see FIGS. 5A-B), as well as when theuser has completed their imaging session and can remove the headset.

FIG. 3 illustrates a further exemplary embodiment of the invention, inwhich the headset also includes a video function that provides the userwith a form of virtual reality entertainment during the imageacquisition process to help the user remain engaged until images havebeen successfully acquired. In this version of the headset (see FIG.3A), one or two displays (one for each eye, e.g., LCD, OLED, and thelike) are located inside the headset goggles. Lenses are placed betweenthe displays and the user's eyes, where the distance between the lensesand eyes can be manually adjusted by the user until the displays' imagesare clear. The displays each include a central opening, through whichthe scanning hardware can image each eye, or for displays formed oftransparent or semi-transparent material, the scanning hardware does notrequire a central opening and scans directly through the display itself.After the user has donned the headset and switched the device toautomatic mode, a video will be played for a brief period of time, afterwhich the screen will turn off and an audible countdown will commence.As an example (see FIG. 3B), the video may show one or more of thefollowing:

1. A cartoon character walking into a movie theater with a bucket ofpopcorn

2. After finding their seat in the theater, the character sits down andthe lights in the theater begin to dim in preparation for the movie

3. Once the theater lights are off, the display(s) will also turn off inthe headset and an audible countdown will commence for the user

4. A red fixation light will be displayed through the central opening ofthe display(s) (or through the transparent or semi-transparent material)and, once the user is fixating, images will automatically be acquiredfrom each eye

5. After image acquisition, the displays will turn on again and show thecharacter watching a movie playing on the theater screen. During thistime, pre-processing algorithms will determine if the images areacceptable (e.g., if a non-significant amount of motion is detected) andeither inform the user (using auditory and/or visual cues) that theimaging session is complete or a re-scan is required.

6. In the case of a re-scan, the light in the theater on the displayvideo will once again dim, and steps 3-5 will be repeated.

Other video content, other than a movie theater, can be displayedinstead of, or in addition to, the exemplary movie theater example.

Data Storage and Transmission

FIG. 4 illustrates how data may be stored and transmitted following auser's imaging session. After image acquisition (see FIG. 5), image data(e.g., in DICOM format) may follow one of several pathways, where dataprocessing and analysis will be automated by a series of imageprocessing algorithms:

Option 1. The data may be immediately pre-processed on the device (seeFIG. 5), transferred to a database server in the cloud for furtherpost-processing and analysis (see FIGS. 5 and 6), and results outputted(e.g., wirelessly) to the user and/or a clinician's mobile softwareapplication. In this case, a limited amount of raw and pre-processeddata (e.g., 1 month's worth of imaging sessions) can be temporarilystored on the device and—after a period of time or after reaching adevice storage limit—transferred (e.g., wirelessly) to the databasecloud server for permanent storage with the post-processed data andanalyzed results.

Option 2. The data may undergo pre- and post-processing on the device,after which it is transferred to a database server in the cloud foranalysis, and results ouputted (e.g., wirelessly) to the user and/or aclinician's mobile software application. In this case, a limited amountof raw, pre-, and post-processed data can be temporarily stored on thedevice and—after a period of time or after reaching a device storagelimit—transferred (e.g., wirelessly) to the database cloud server forpermanent storage with the analyzed results.

Option 3. In yet further embodiments, pre-processing can be performed atthe (cloud) server level, with the raw data being communicated to thatserver without preprocessing. In this case, the device will communicatewith the server to obtain the amount of eye movement detected in theimages (as calculated during pre-processing)—this information will beused by the device to determine whether the imaging session wassuccessful or if a re-scan is needed.

Option 4. Furthermore, raw and/or pre- and/or post-processed data canoptionally not be stored for significant time periods on the datacapturing system itself, instead being stored at the server level, thedata capture system storing the data locally only for time sufficient totransmit that data upstream towards the server level.

Data Processing and Analysis

FIG. 5 illustrates a set of image processing algorithms used to assessimages acquired with the device. Image pre-processing (see FIG. 5) mayinclude motion detection (where re-imaging is automatically initiated orthe user is prompted to manually acquire a new image set [using the“Acquire Image” button] if execessive motion is detected), motioncorrection, denoising, and luminance normalization. The extent of eyemotion may be determined by calculating the spatial difference betweentwo consecutive images across the series, where a significant amount ofmotion, for example, can be defined as an eye movement ≥2.4 μm or ≥2%change in image signal intensities from the 1^(st) acquired image to thelast. Pre-processing will be accomplished using an image processingalgorithm that is programed into the device's signal processing unit.After image acquisition, the pre-processing algorithm can also be usedto measure light levels, pupil size, and image contrast (resulting fromdifferences in fundus opacity), and automatically incorporate thesemeasures into the pre-processing scheme.

Post-processing (see FIG. 5) of the OCT images may include alignment ofA-scans to obtain a B-scan, gray-level mapping and direction filteringto enhance retinal layer edges, and identification of layer contours inthe B-scan images using an edge detection kernel. Post-processing of theFAF images may include transforming the data into grayscale intensityimages. Post-processing can be accomplished using either an imageprocessing algorithm that is programed into the device's signalprocessing unit or using an image processing algorithm that resides on adatabase cloud server.

FIG. 6 illustrates a series of image processing algorithms used toanalyze the post-processed images in order to identify significantspatial and temporal changes in the user's retinal pathology (e.g.,retinal layer thicknesses and autofluorescence) over time; data analysiscan be accomplished using an image processing algorithm that resides ona database cloud server.

FAF image analysis may include, but is not limited to, the followingsteps: automatic segmentation of the retina to detect various featuresincluding vasculature and the fovea, a histogram analysis of signalintensities across the retinal field of view (FOV), localization ofhyper- and hypofluorescence intensities, and correlation analysis ofsignal intensities over time (e.g., by comparing results with previousacquisitions) for the whole retina and for individual regions ofinterest (ROIs). The resulting output to the mobile software applicationcan include graphs of autofluorescence intensities over time and alertsdescribing any significant changes in autofluorescence over time.

OCT image analysis may include, but is not limited to, the followingsteps: automatic segmentation of the B-scan cross-sectional images toidentify different retinal layers, calculation of thickness measurementsfor each layer, and correlation analysis of changes in thickness of eachlayer over time (e.g., by comparing results with previous acquisitions).The resulting output to the mobile software application can includegraphs of retinal layer thicknesses over time and alerts describing anysignificant changes in thickness over time.

In order to localize changes in autofluorescence (e.g., representingmicroglial activity and inflammation, or atrophy) to specific retinallayers, a combined FAF and OCT image analysis can be conducted that mayinclude, but is not limited to, identification of retinal coordinatesfor ROIs that contain changes in both autofluorescence and retinal layerthickness, and a correlation analysis to determine if the two measureschange together over time for a particular region. For example, in thecase where an ROI includes an increase in autofluorescence and anincrease in “layer A” thickness, a conclusion may be drawn that “layerA” is experiencing an increase in inflammation. The resulting mobilesoftware application output can include interpretations of the OCT/FAFanalysis, including which retinal layer(s) may be experiencinginflammation or degeneration, and what brain pathologies these changesmay reflect.

An additional machine learning-based analysis may be used to identifysignificant correlations between user-inputted data (e.g., changes insymptoms and changes in medication) and changes in FAF and/or OCTmeasurements. The resulting mobile software application output caninclude symptom predictions based on changes in retinal pathology, andthe effect of changes in medication on retinal pathology (e.g., diseaseactivity).

Accompanying Mobile Software Applications

Multiple versions of the mobile software application can be used,including, but not limited to, a patient version and a clinicianversion.

The patient mobile app (see FIGS. 1B and 14) is for patient use andeither 1) provides a summary of the user's disease activity based on theOCT and FAF measurements, 2) reminds the user to use the device andprovide confirmations when images have been successfully delivered to aclinician, and/or 3) alerts the user to any changes in system status(e.g., a low device battery or recent mobile software update). Thesummary of disease activity can include the following information:

1. Alerts for significant changes in inflammatory activity orneurodegeneration

2. Predictions of symptom changes

3. A summary of OCT and FAF measurements in graphical display form,including any user-inputted changes in medication (e.g., date amedication was initiated, ended, or changed).

The clinician mobile app (see FIG. 7) can provide both raw andpost-processed data, as well as analyzed results, for clinicians to usein monitoring any patient with a system; clinicians will be able totrack multiple patients at once using the clinical mobile app. Similarto the patient version, it can provide automatic alerts of anysignificant changes in measurements acquired by a patient over time.This will enable clinicians to monitor their patients' disease activityremotely and provide an additional layer of reassurance for the patientby allowing a clinician to immediately confirm whether or not asignificant change in measurements should warrant a follow-up clinicalvisit, change in medication, and/or additional tests.

Variations in Hardware Component Configuration

1. Headset-Only FAF-Only Configuration

FIG. 8 illustrates an FAF-only version of the device that is integratedinto a headset module. Within the figure, solid lines indicate anelectrical connection between the microcontroller unit and differentcomponents of the device, dashed lines indicate free light pathways, andthe back of the user's eye, representing the retina, is marked by a darkarc.

Step 1. Fundus Image Acquisition: Once image acquisition is initiatedmanually by the user or automatically by the device, broadband light isemitted from a light source (11 a), which is advantageously an LED,through an aperture (12), and directed through a lens system (19) to theuser's eye using a beam splitter (13). Light reflected from the user'sretina (i.e., the fundus image) then travels back through the lens andbeam splitter, through an additional autofocus lens (14), and isdirected through a secondary aperture (12) to a camera (16) (e.g.,mini-CMOS) using a beam splitter (13). The camera then captures thefundus image and transmits it to a signal processing unit (22) forpreprocessing. A microcontroller unit (20) is used to implement thefundus illumination scheme (e.g., turning the light source on for aspecific amount of time and removing an emission barrier filter (15)during fundus image acquisition). A power supply (21) is used to powerthe microcontroller unit, which can include a battery. The emissionbarrier filter (15) is removed from the free-space light path using amotorized filter wheel or motorized filter flip mount (not illustrated)prior to fundus image acquisition.

Step 2. FAF Image Acquisition: Immediately after a series of fundusimages are acquired, the microcontroller unit moves the emission barrierfilter (15) back into the path of light. The same sequence as describedabove is then used to capture FAF images of the user's retina.Differences include: emitting a specific wavelength of light (e.g., 470nm or 535-585 nm for lipofuscin excitation) from the light source (11 a;or, alternatively, passing broadband light through an excitation filterimmediately before or after the aperture (12) to obtain a specificwavelength) and passing the reflected light from the user's retinathrough the emission barrier filter (which isolates the wavelengths oflight emitted from lipofuscin [e.g., 600-610 nm]) before passing throughthe secondary aperture (12).

A signal processing unit (22) with wireless, Bluetooth, and/or othernear-field communication (NFC) capabilities is controlled by themicrocontroller unit and used to pre-process the raw fundus, FAF, andOCT image data and transfer pre- and/or post-processed image data to adatabase server, which is advantageously a cloud server.

FIG. 9 illustrates an example 3D rendering of the FAF-only opticalimaging component (see FIG. 9A) and how it is integrated into a headset(see FIG. 9B), where dark solid lines illustrate the fixation targetlight directed out of the device (on left) and towards the user's eye,and white lines indicate electrical connections. An additional beamsplitter may be included on the left side of the device (hidden fromview) in order to direct the light outward toward the user's eye.Identical versions of FAF-only imaging components are integrated intoboth sides of the headset goggles for consecutive scanning of both eyes(where the illustration image shows approximate scale of the hardwarewith-respect-to the goggles). All components are hidden from the user,such that only the fixation target light is visible to each eye.

2. Headset-Only FAF/TD-OCT Configuration

FIG. 10 illustrates an FAF/OCT version of the device that utilizes atime-domain form of OCT (i.e. TD-OCT) and is integrated into a headsetmodule (identical versions of FAF-TD-OCT imaging components areintegrated into both sides of the headset goggles). Arrows indicate themotion of mobile components in the device. The embodiment of FIG. 10 issimilar in some respects to that of FIG. 8 and includes some similarcomponents.

Step 1. Fundus Image Acquisition: A microcontroller is used to control amotorized MEMS scanning reference mirror (17) and motorized transversescanning mirror (18). Prior to fundus image acquisition, themicrocontroller places both mirrors in fixed positions. Fundus imagesare then acquired using the same sequence described for the FAF-onlydevice.

Step 2. FAF Image Acquisition: Immediately after a series of fundusimages are acquired, FAF images are acquired in the same manner asdescribed for the FAF-only device. The scanning mirrors remain in afixed position.

Step 3. TD-OCT Image Acquisition: Immediately after a series of FAFimages are acquired, the microcontroller unit 1) positions the twoscanning mirrors at their starting positions (which may or may not bedifferent from the positions used for fundus and FAF image acquisition),and 2) removes the emission barrier filter out of the path of light. Thesame sequence as described for the FAF-only device is then used tocapture TD-OCT images of the user's retina. Differences include:emitting a low coherence light from a superluminescent diode (11 b)—thislight emission is synchronized with axial scanning of the referencemirror (17) to acquire axial depth (A-scan) images, and transversescanning of the transverse mirror (18) to combine the A-scan images intoa 2D cross-sectional image (B-scan) of the whole retina. While the diodeis turned on, synchronization can be achieved by using themicrocontroller unit to trigger a sweep of the scanning reference mirrorfor every step of the transverse mirror, until a series of A-scans havebeen acquired across a retinal ROI. OCT scanning can be synchronizedwith data acquisition using a signal from the microcontroller thatsimultaneously triggers scanning of the mirrors and acquisition of theresulting A-scan.

3. Headset-Only FAF/SS-OCT Configuration

FIG. 11 illustrates an FAF/OCT version of the device that utilizes aswept-source form of OCT (i.e. SS-OCT) and is integrated into a headsetmodule (identical versions of FAF—SS-OCT imaging components areintegrated into both sides of the headset goggles). The embodiment ofFIG. 11 is similar in some respects to that of FIGS. 8 and 10 andincludes some similar components.

Step 1. Fundus Image Acquisition: Prior to fundus image acquisition, themicrocontroller places the transverse scanning mirror (18) in a fixedposition. Fundus images are then acquired using the same sequencedescribed for the FAF-only device.

Step 2. FAF Image Acquisition: Immediately after a series of fundusimages are acquired, FAF images are acquired in the same manner asdescribed for the FAF-only device. The transverse scanning mirrorremains in a fixed position.

Step 3. SS-OCT Image Acquisition: Immediately after a series of FAFimages are acquired, the microcontroller unit 1) positions thetransverse scanning mirror at its starting position (which may or maynot be different from the position used for fundus and FAF imageacquisition), and 2) removes the emission barrier filter out of the pathof light. The same sequence as described for the TD-OCT-only device isthen used to capture SS FD-OCT images of the user's retina. Differencesinclude: emitting a narrow band of wavelengths using a tunable laserlight source (11 c)—this sweeping light emission is synchronized withscanning of the transverse mirror (18) to quickly acquire A-scan images,which are then combined during post-processing into a 2D cross-sectionalimage (B-scan) of the whole retina.

4. Headset and Tabletop SS-OCT-Only Configuration

FIG. 12 illustrates an SS-OCT-only version of the device that isintegrated into a tabletop module (A) and headset (B) (see FIG. 14),where the heaviest components are housed in the tabletop module (e.g., a12×6×7 in box). Dashed lines indicate free light pathways, black linesindicate fiber optic cables, and thin gray lines indicate electricalconnections. The SS-OCT design includes identical optical systems foreach eye, which allow for consecutive scanning of both eyes within theheadset unit. These components are housed in a pair of lightweight anddurable goggles with adjustable straps, which can be similar to thosedescribed elsewhere herein.

The tunable laser (e.g., with 1060 nm center wavelength and 100 kHzsweep rate [i.e. 100k A-scans/s]) (11 c) delivers a spectrum of lightvia fiber optic cables through a circulator (22) to a 2×2 fiber coupler(23), where the beam is split and guided to 1) the reference arm (e.g.,formed of a collimator (24), achromatic doublet lens (25), and staticsilver-coated reference mirror (26)) and 2) through a collimator to amotorized flip mirror (27). To allow for consecutive imaging of eacheye, a multifunction reconfigurable I/O module with FPGA (30) is used tocontrol the motorized flip mirror, such that the beam is directed towardthe eye being imaged in the sample arm (located in the headset unit).The module is further used to control the MEMS scanning micromirrors(28) during imaging, which steer the sample beam laterally through atelecentric scan lens (29) and across each retina.

Reflected beams from the reference arm and sample arm are re-combined atthe 2×2 fiber coupler and the resulting OCT signal is detected by abalanced photodetector (e.g., with a bandwidth of at least 200 MHz)(31). The OCT signal is then digitized by the multifunction module,including fast Fourier transform of the signal to obtain an A-scan. OCTscanning is synchronized with data acquisition using 1) a trigger signalfrom the tunable laser that triggers acquisition of the resulting axialscan (i.e. A-line), and 2) a K-clock signal from the tunable laser thatwill be used to trigger sampling of the OCT signal at evenly spacedoptical frequencies.

5. Headset and Tabletop FAF/SS-OCT Configuration

FIG. 13 illustrates an FAF/SS-OCT version of the device that isintegrated into a headset and tabletop module (see FIG. 14). Theheaviest SS-OCT and FAF elements are housed in the tabletop unit. Dashedlines indicate free light pathways, black lines indicate single-modefiber (SMF) optic cables, gray double lines indicate double-claddingfiber (DCF), and thin gray lines indicate electrical connections. Theembodiment of FIG. 13 is similar in some respects to that of FIG. 12 andincludes some similar components.

A broadband LED and tunable laser (e.g., with 1060 nm center wavelengthand 100 kHz sweep rate [i.e. 100k A-scans/s]) can serve as the FAF andOCT light sources, respectively. Visible light from the broadband LEDfirst travels through an excitation filter (e.g., 535-585 nm forlipofuscin excitation; 38) before being combined with near infrared(NIR) light from the tunable laser at a 2×1 wavelength divisionmultiplexer (WMD) coupler (33) and into a SMF cable for sequential FAFand OCT imaging. These beams are then split using a 50:50 SMF coupler(34) and transmitted to the 1) reference arm (e.g., consisting of acollimator, achromatic doublet lens, and static silver-coated referencemirror) and 2) headset sample arm via the through-port of a DCF coupler(37). Use of DCF enables us to implement an all-fiber OCT/FAF systemthat can achieve simultaneous FAF and OCT image acquisition for eacheye.

The headset includes identical optical systems consisting of atelecentric scanning lens, MEMS scanning micromirror, and collimator. Toallow for consecutive imaging of each eye, the multifunction module isused to control the motorized flip mirror, such that the beams aredirected toward the eye being imaged. OCT (NIR light) and FAF (visiblelight) beams from the tabletop unit sequentially enter either the rightor left side of the headset via 1 of 2 SMF cables and are directed by acollimator to a MEMS scanning micromirror.

For OCT imaging, reflected OCT beams from both reference and sample armsare re-combined at the 50:50 SMF coupler and the resulting OCT signal isdetected by a balanced photodetector (e.g., with a bandwidth of at least200 MHz). The OCT signal is digitized by a multifunction module withFPGA, including fast Fourier transform of the signal to obtain anA-scan. OCT scanning is synchronized with data acquisition using 1) atrigger signal from the tunable laser that triggers acquisition of theresulting axial scan (i.e. A-line), and 2) a K-clock signal from thetunable laser that is used to trigger the sampling of the OCT signal atevenly spaced optical frequencies.

For FAF imaging, the reflected visible light from the sample arm isdirected through the cross port of the DCF coupler and through a barrieremission filter (e.g., 615-715 nm to isolate fluorescent emissions fromlipofuscin on the retina; 35). The filtered beam is then directed to aphotomultiplier light detector (36) and processed by the multifunctionmodule.

FIGS. 15A, 15B, and 15C illustrate other exemplary embodiments, in whichthe headset (1) includes only a single optical imaging component (40)mounted in the headset (see FIG. 15A). In these single-componentembodiments, the single optical imaging component can be mounted asillustrated in FIG. 9B and FIG. 15A, that is, for direct interactionwith one of the patient's eyes, and the goggles include one or moreoptomechanical elements (e.g., translation stage, rails (39), driver,motor, actuator, and/or motorized wheel) in the light path so that thecontroller can switch the light path emanating from the single opticalimaging component from being directed at the eye at which the componentis mounted, to being directed at the eye at which the component is notmounted. Further optionally, other embodiments can similarly includeonly a single optical imaging component, but that component is notmounted as illustrated in FIG. 9B, i.e., for direct interaction witheither of the patient's eyes, but instead is mounted elsewhere in theheadset (see FIG. 15B). In this second set of embodiments, the gogglesinclude a pair of sets of one or more optical elements (e.g., a galvomirror system, additional MEMS scanning micromirror (28) and/ormotorized flip mirror (27)) in the light path of the single opticalimaging component, so that the controller can switch the light pathemanating from the single optical imaging component to be selectively,and sequentially, directed at the left or right eye. According to yetanother set of embodiments, instead of goggles which are sized andconfigured to fit over both eyes of a patient, a monocle-like goggle,which fits over only one eye, can be used, with a single optical imagingcomponent mounted therein as otherwise described herein (see FIG. 15C).In this exemplary monocle (or “goggle”) set of embodiments, theprotocols are modified to instruct the patient to move the device fromone eye, after image acquisition is complete, to the other eye, for dataacquisition.

ADDITIONAL CONSIDERATIONS

In all examples of the devices and methods described herein, a safetymechanism is built-in to prevent the user from being overexposed to thelight source. This may include programming the multifunction module tolimit the frequency and duration of use of the light source (e.g.,tunable laser) such that the device only acquires a certain number ofimages within a certain time frame.

In addition, spectral-domain OCT (SD-OCT) may be used in place of SS-OCTin the above configurations. This would require replacement of thetunable laser with a broadband light source and use of a spectrometerinstead of a balanced photodetector.

Prior to image acquisition, each configuration of the device produces afixation target (e.g., red light) that originates from the tunable laserin SS-OCT-only configurations, and from the broadband LED inconfigurations that include FAF imaging. The fixation light and audiblecountdown are synchronized by the microcontroller or multifunctionunits. The audible countdown is programed into the multifunction unitand presented using a speaker that is integrated into the headset, forwhich the system includes appropriate amplifiers. During fixation, thedevice also automatically focuses on the user's retina (e.g., usingautofocus scan lenses in the sample arm that are controlled by themultifunction unit).

Eye-tracking to determine when the user's gaze is steady and ready forimage acquisition is achieved using an optical tracking technique, whereinfrared light from the tunable laser is sent to one or both eyes in thesample arm. The reflected light from the eye is then detected by anoptical sensor (e.g., the balanced photodetector) and pre-processed bythe multifunction unit to determine when the user is fixating (e.g.,when their gaze remains within a diameter of 1° visual angle for atleast 100 ms).

In all examples, the headset includes a rechargeable battery with a USBport (FIG. 1A) and charging circuitry that powers the multifunction unitand all electrical components in the device. The tabletop unit may alsoinclude a rechargeable battery.

Example Applications

A first application of the systems and methods described herein will beto multiple sclerosis (MS) patients.

MS is a debilitating chronic inflammatory disease in which the body'simmune system attacks the protective myelin sheath surrounding nervefibers, causing damage to the central nervous system (CNS)—including theretina. This recurring inflammatory response and neurodegenerationproduces symptom relapses and long-term disability, including weakness,pain, spasms, and cognitive disability. MS affects nearly 1 millionpeople in the US and more than 2.5 million people worldwide, with mostindividuals being diagnosed between 20-40 years old. 85% of MS patientsare diagnosed with a relapsing-remitting form of the disease (RRMS).RRMS is characterized by unpredictable and transient MS attacks: theappearance of active inflammatory lesions and scar tissue (sclerosis)within the CNS that may be asymptomatic or accompanied by highlyvariable symptoms. Without effective treatment, the majority of RRMSpatients ultimately transition to secondary-progressive MS (SPMS), withsymptoms worsening more steadily over time, and for which there arecurrently no FDA-approved therapies.

Early detection of disease activity and proper treatment of RRMS iscrucial to reducing the risk of disease progression and accrual ofdisability. Current practice relies on 1-2 annual clinical visits andmagnetic resonance imaging (MRI) of the CNS to assess changes in diseaseactivity and the efficacy of a patient's treatment regimen.However—other than patient reporting of symptoms—there is currently noway to monitor MS between these periodic visits, increasing thelikelihood that new untreated inflammatory activity in the CNS resultsin permanent neuronal damage. This is especially true of the 80-90% ofnew lesions that are asymptomatic and result from subclinical diseaseactivity. Since symptomatic relapses vary in type, length, and severity,patients do not always recognize and report an MS exacerbation (attack),further hampering a physician's ability to intervene in a timely manner.The resulting delay in treating MS activity in RRMS patients has beenshown to have a negative impact on MS prognosis, including a decline inquality of life and functional ability.

The systems and methods described herein can improve clinical practiceby addressing the critical unmet need for more effective and frequent MSmonitoring. Information captured by the device provides patients andphysicians alike with an objective means of tracking disease activity.This in turn helps patients identify MS disease processes (includinginflammatory activity) and encourage them to immediately report these totheir physician, and/or the data is automatically reported to theclinician. Clinicians in turn use the measurements to help determine ifa treatment is effective based on retinal changes that occur betweenclinical visits, and/or if additional or new therapy, including but notlimited to medication (e.g., a steroid course, change in amount and/ortype of medication, and combinations thereof). The result is earlierdetection of MS activity and more efficient monitoring of treatmentefficacy, leading to shorter-term use of ineffective drugs and likely afurther reduction in risk of disease progression due to earlierintervention. Specifically, use of the device is beneficial toindividuals with clinically isolated syndrome (CIS) who have not yetbeen diagnosed with MS, newly diagnosed MS patients, individualsexperiencing a relapse, and patients with a recent change in treatmentregimen.

In an alternative embodiment, the systems and methods can also beapplied to patient groups with any condition that presents in theretina. Example target markets include:

Neuroinflammatory Diseases. Data gathered and/or produced by the systemsand methods described herein may be used to monitor any neurologicaldisease that is characterized by an inflammatory reaction in the centralnervous system and manifests (structurally and/or functionally) in theretina. This may include (but is not limited to) the following diseases:Multiple Sclerosis (MS), Parkinson's disease, Alzheimer's disease, Acutedisseminated encephalomyelitis (ADEM), Optic Neuritis (ON), TransverseMyelitis, and Neuromyelitis Optica (NMO).

Neurodegenerative Diseases. Data gathered and/or produced by the systemsand methods described herein may be used to monitor any neurologicaldisease that is characterized by an atrophy of the central nervoussystem and manifests (structurally and/or functionally) in the retina.This may include (but is not limited to) the following diseases:Dementias, Prion disease, Motor neuron diseases (MND), Huntington'sdisease (HD), Spinocerebellar ataxia (SCA), Spinal muscular atrophy(SMA), and Amyotrophic lateral sclerosis (ALS).

Retinal Inflammatory Diseases. These include (but are not limited to)age-related macular degeneration (AMD), diabetic retinopathy (DR), andglaucoma. Symptoms and pathology for these diseases are directly relatedto changes in retinal inflammation, such that the systems and methodsdescribed herein can be used to help patients monitor their conditionsand response to treatment at home.

Research Groups. Data gathered and/or produced by the systems andmethods described herein may be used as an additional outcome measureduring studies of retinal, neurodegenerative, or other diseases. Sincethe device can be used in subjects' homes, groups can gather a greaterdepth of temporal data describing patient treatment responses, includingin rural and developing country sites with limited access to retinaland/or brain imaging equipment. In some cases, the device will helplower study costs by requiring fewer site visits if similar data can beacquired with the system in a patient's home. There are currently morethan 3,600 open clinical trials for retinal and corticalneurodegenerative diseases worldwide led by pharmaceutical companies andresearch institutions.

Traumatic Brainy Injury. Neuroinflammation is a major cause ofbehavioral and eye/brain pathological changes following TBI (includingconcussion). The systems and methods described herein can be used bypatients at home and by military in the field.

Epilepsy. Studies have demonstrated that neuroinflammation initiatesseizures and that this immune response can be detected in the retina.Monitoring is crucial to epilepsy patients with recurring seizures.

Addiction. Neuroinflammatory responses are a known consequence of drugand alcohol abuse. Monitoring of inflammation can help track patientresponses to treatment and help determine patient risk of relapsepost-treatment.

In addition, the systems and methods described herein can be used byotherwise healthy individuals to monitor their brain health at home as apreventative measure, particularly among the elderly. In this case, thesystem may be used as described or with the following change: instead ofautomatic data transfer to a clinician, the user may instead be alertedwhen significant changes in retinal structure or function have beendetected that should be shared with a clinician. The user can then usetheir mobile software app to export and/or share processed data andanalyzed results with their doctor.

Example Protocol for Use by a Patient (see FIG. 14)

The following is an exemplary protocol of how the systems and devicesdescribed herein can be used by a patient at home, as well as by theirphysician during clinical visits. This example does not include use ofan optional virtual reality option.

Daily Use at Home: Image Acquisition

Each morning, the patient will place the goggles on their head such thatthe strap is comfortably adjusted to their head size and little-to-nolight is escaping past the black goggle shield (FIGS. 1C and 14).

The patient will turn the device on using the power button on the sideof the goggles (FIG. 1A).

An audible countdown from “ten” to “one” will commence while thepatients' eyes naturally dilate as they adjust to the darkness of theheadset (where dilated eyes will enable the camera to see and capturebetter images of the retina).

At the end of 10 seconds, a red fixation light (originating from thesystem's light source) will turn on in the goggles for the patient tofixate on (in order to reduce any eye movements that could interferewith clear image acquisition).

If the device is in automatic mode, the device will automaticallyacquire fundus, FAF, and/or OCT images once it detects a steady gaze, asidentified by the multifunction module, signal processing unit, orcloud-based image processing software.

If the device is in manual mode, the patient will press the acquisitionbutton on the side of the device once he/she is ready for the device tocapture images (i.e., they are ready to hold their gaze steady for a fewseconds).

Immediately prior to image acquisition in both cases, the red lightsadvantageously, although optionally, blink one or more times to warn thepatient that the device will soon capture images and to keep their gazeas steady as possible.

After the images have been captured, all lights in the device will turnoff, leaving the patient in a brief darkness.

The device's multifunction unit (or signal processing unit, orcloud-based image processing software) will immediately calculate theamount of eye movement across the series of images (e.g., by calculatingthe signal intensity difference between two consecutive images acrossthe series, where a significant amount of motion is indicated by asignificant change in pixel locations or change in image signalintensities from the 1^(st) acquired image to the last).

If a significant amount of motion is detected, the device will turn thered fixation light back on and/or give a verbal cue to indicate thatimage acquisition was not successful and that the images need to bere-acquired. The patient will then repeat the process.

If a non-significant amount of motion is detected, the device will turna green light on and/or give a verbal cue to indicate that imageacquisition was successful.

Once the patient receives a green light, they will remove the gogglesand turn off the device using the power button. Alternatively, thedevice will turn off by itself following a period of non-use.

This entire process should last no more than five minutes, howevershorter or longer times can also be used.

Daily Use at Home: Syncing with the Mobile App and Inputting User Data

Immediately after image acquisition or later the same day, the patientwill turn on the device using the power button and open the app on theircomputing, e.g., PC or mobile, device. If the device is in range and on,the mobile app will automatically sync with the device. This syncingprocess will include: wireless transfer of the pre-processed and/orpost-processed image data to a database cloud server, analysis of theimages, and transfer of the results (including graph updates) to themobile app.

Once syncing is complete, the patient is preferably guided through aseries of app pages that helps the patient to easily report the locationand intensity of any new symptoms or changes in existing ones.

In addition, the patient can input any changes in medications and/orsupplements, as well as the dates of any recent clinical visits.

The patient mobile app can then provide simple text to help the patientunderstand the significance of their results, including:

Trends over time (for example, in the case of an increase inautofluorescence intensity over time following a change in prescription,the app may say “Your disease activity has increased since you startedyour new medication. You may want to contact your doctor to determine ifyour prescription should be changed”).

Alerts to any significant changes in disease activity (for example,“Your inflammation has been steadily decreasing—you may be entering aperiod of MS remission”).

Predictions based on historical trends (calculated by the software onthe database cloud server) between the patient's retinal measurementsand inputted symptoms (for example, “Your disease activity has beenincreasing over the past 2 weeks. Based on your past trends, you mayexperience a symptom exacerbation soon”).

Physician Use at the Clinic: Transmission of Data to a Clinician

After the patient has finished inputting any additional relevant data,the results from their data acquisition will be automatically sent totheir clinician for remote review.

The patient will be notified when the transmission has been received bythe clinician.

The clinician will then be able to view the following information abouttheir patient using the clinician mobile software app:

Changes in autofluorescence over Y period of time—this may be labeled as“Estimated Brain Inflammation or Atrophy from FAF”

Changes in retinal thicknesses over Y period of time—this may be labeledas “Estimated Brain Inflammation or Atrophy from OCT”

Estimated changes in autofluorescence for specific retinal layers over Yperiod of time—this may be labeled as “Estimated Brain Inflammation orAtrophy from FAF+OCT”

These graphs will also include any prescription compliance-related dataadded by the patient.

Based on the results received, the physician will determine if anychanges in retinal pathology warrant a change in treatment regimen orfollow-up visit. Additionally, the physician can prescribe one or moretherapies including, but not limited to medications, including but notlimited to steroids, vitamins, immunosuppressives, and anti-inflammatorydrugs, and the patient then takes those therapies; alternatively, thephysician can instruct the patient to stop one or more therapies thepatient is currently taking; or combinations of these two. Thereafter,the patient again uses the systems and methods as described herein at alater time, and the physician can assess the efficacy of that newregimen; this cycle can be repeated.

Device Hardware Specifications

Device Packaging (FIGS. 1A and C, FIG. 14): exemplary devices can haveone or more of the following attributes.

A device that is portable and can be used by the patient at home andwhile traveling

A device with packaging that includes a headset that fits the majorityof faces, for comfort and ease-of-use by the user

A device with lightweight packaging

A device with durable and ruggedized packaging (including to withstandfluctuations in acceleration, temperature, humidity, and shock)

A device with custom headset packaging that reduces or eliminatesoutside light to allow the user's pupils to naturally dilate, thusenhancing the quality of images acquired by the device

A device with packaging that provides a target for the user to easilyfixate on while operating the device (to help reduce significant eyemovements during image acquisition)

A device with packaging that conceals all image acquisition andprocessing components from the user

A device with buttons to activate the system that are easilydistinguished by touch

A device with buttons that allow the user to choose either manual orautomatic image acquisition

A device with voice commands that guides the user through the imageacquisition process and use of the device

A device with a rechargeable battery

A device with built-in safety measures to prevent overuse andoverexposure of the user to the light source(s), such as automaticallyturning the device off after some time of not being used

Device Image Acquisition: exemplary devices can have one or more of thefollowing attributes.

A device that captures fundus images of the retina

A device that captures FAF images of the retina, including images ofregions with hyperfluorescence and hypofluorescence

A device that captures OCT images, including cross-sectional images ofthe retina to measure layer thicknesses

A device that captures only FAF images, only OCT images, or both

OCT will be implemented either in the time-domain (TD-OCT, FIG. 10) orFourier-domain (FD-OCT, FIGS. 11-13)

A device that is able to acquire fundus, FAF, and OCT images in quicksuccession or simultaneously

A device that can capture images in undilated (non-mydriatic) eyes

A device that can automatically detect when the user is fixating

A device that is able to automatically focus on the user's retina as theuser fixates on a target

A device that can also measure other relevant information about theuser's eye, including light levels in the headset, pupil size, andfundus opacity (i.e. image contrast)

A device that uses a light source that is safe for use in humans,according to ISO and ANSI standards for light safety

A device that acquires image data in a common image format (e.g., DICOM)

Image Processing (FIGS. 5B-C): exemplary systems can have one or more ofthe following attributes.

A system (defined as the device, a cloud server, a mobile softwareapplication, or combinations thereof) that temporarily stores theresulting raw fundus, FAF, and OCT images

A system that uses signal and image processing algorithms to pre-processthe raw image data, including: motion detection and correction, signalfiltering to remove noise, signal enhancement (including image contrastadjustment and luminance normalization)

A device that is able to detect when images contain a significant amountof motion and are not interpretable (for example, using an eye-trackingalgorithm)

A device that notifies the user to re-acquire the images if significantmotion is detected

A device that is able to (e.g., wirelessly) transmit the pre-processedimage data to a cloud server or mobile software application

Image Data Analysis (FIG. 6): exemplary systems can have one or more ofthe following attributes.

A system that wirelessly transmits pre-processed images from the deviceto a cloud server and/or mobile software application

A system that contains an image post-processing and analysis algorithmthat extracts the following FAF and OCT measures, respectively:

Quantification of hyper- or hypofluorescent intensities across theuser's retina, including the coordinate location of intensities above orbelow a specified threshold

Quantification of retinal layer thicknesses across the retina, includingthe coordinate location of thicknesses above or below a specifiedthreshold

A system that combines FAF and OCT measures to provide an estimate ofwhich retinal layers are experiencing a change in autofluorescence(i.e., inflammation or atrophy)

A system that automatically co-registers images of the retina frommultiple acquisition sessions (for comparison of FAF and OCT measuresover time)

A system that generates graphs of FAF, OCT, and FAF+OCT measures overtime, including—changes in autofluorescence intensity, changes inretinal layer thicknesses, changes in estimated autofluorescenceintensity for each retinal layer

A mobile app that automatically updates the above graphs each time newimage data is acquired and analyzed

A mobile app that identifies changes in FAF and OCT measures that aresignificantly related to user-inputted data (such as time since amedication was changed)

Mobile Software Specifications (for the clinician and/or patient mobileapps): exemplary devices can have one or more of the followingattributes.

Example patient (FIGS. 1B and 14) and clinician (FIG. 7) mobile softwareapplication user interfaces

A mobile app that includes a user-friendly interface

A mobile app that saves X amount of analysis results for Y daysdepending on the user's chosen subscription plan

A mobile app that provides users with raw, pre-, and post-processedfundus, FAF, and OCT images of the retina (acquired within Y days)

A mobile app that provides users with a graphical illustration ofchanges in FAF and OCT measures over time

A mobile app that allows users to easily input information that can betracked alongside any significant changes in FAF and OCT measures,including: date when a new medication is started, date when a medicationis stopped or dosage changed, onset of a new symptom, date when asymptom increases or decreases in intensity/severity, and date of lastclinical visit

A mobile app that alerts the user to any changes in FAF and OCT measures(i.e., disease activity)

A mobile app that provides symptom predictions to the user based onchanges in FAF and/or OCT measures

A mobile app that includes a community discussion board for any device,app, or health-related questions

A mobile app that provides patients with reminders to use the deviceregularly

A mobile app that notifies the user when data has been successfullytransmitted or received

A system that allows remote monitoring of retinal pathology andassociated neurological disease

A system that can provide both functional and structural assessment ofthe retina

In yet further embodiments, the applications describes as being executedon mobile devices can instead be implemented to be displayed via a webbrowser running on a general purpose computing device, e.g., as webcontent which is accessed by the patient, the clinician, or both overthe internet.

Computing devices, including mobile devices and/or servers, describedherein can include one or more of a display device, a keyboard, apointing device, a network connection, processor, video adapter, systemmemory, network interface, serial port interface that arecommunicatively linked together by a system bus. The system memory caninclude read only memory (ROM) and random access memory 3226. A basicinput/output system (BIOS) is stored in ROM. The BIOS can contain basicroutines that help to transfer information between elements/subsystemswithin the computer during certain computer operations. A number ofprogram modules, components, and/or engines can be temporarily stored inthe RAM, such as an operating system, a component control engine, and acomponent database. Permanent storage for the program modules,components, and/or engines described herein can be provided by one ormore types of storage media interfaced to the computer including, butnot limited to, a hard disk drive, an optical disk drive, magnetic diskdrive, flash memory cards, etc. In another embodiment, permanent storagefor the program modules, components, and/or engines can be provided byone or more distributed computing devices (e.g., application servers,database servers, etc.) that are communicatively connected to thecomputer via a network connection.

REFERENCES

-   1 Saidha S, Sotirchos E S, Oh J, et al. (2013) “Retinal axonal and    neuronal measures in multiple sclerosis reflect global CNS    pathology.” JAMA Neurol. 70(1):34-43.-   2 Ahl M, Avdic U, Skoug C, et al. (2016) “Immune response in the eye    following epileptic seizures.” J. Neuroinflammation. 13:155.-   3 Xu L, Nguyen J V, Lehar M, et al. (2016) “Repetitive mild    traumatic brain injury with impact acceleration in the mouse:    Multifocal axonopathy, neuroinflammation, and neurodegeneration in    the visual system.” Exp. Neurol. 275:436-449.-   4 Wang N K, Fine H F, Chang S, Chou C L, Cella W, Tosi J, et al.    Cellular origin of fundus autofluorescence in patients and mice with    a defective NR2E3 gene. Br J Ophthalmol. 2009; 93(9):1234-40.-   5 Brar M, Kozak I, Cheng L, Bartsch D U, Yuson R, Nigam N, et al.    Correlation between spectral-domain optical coherence tomography and    fundus autofluorescence at the margins of geographic atrophy. Am J    Ophthalmol. 2009; 148(3):439-44.-   6 Chung H, Park B, Shin H J, Kim H C. Correlation of fundus    autofluorescence with spectral-domain optical coherence tomography    and vision in diabetic macular edema. Ophthalmology. 2012;    119(5):1056-65.-   7 Cirrus photo. Carl Zeiss Meditec, Inc. Cited Dec. 2, 2017.    Available from:    https://www.zeiss.com/meditec/us/products/ophthalmology-optometry/glaucoma/diagnostics/fundus-imaging/cirrus-photo.html#more-information.-   8 Spectralis. Heidelberg Engineering Inc. Cited May 5, 2018.    Available from:    https://business-lounge.heidelbergengineering.com/us/en/products/spectralis/.-   9 3D OCT-2000 FA plus. Topcon. Cited Dec. 2, 2017. Available from:    http://www.topcon.co.jp/en/eyecare/products/product/diagnostic/oct/3DOCT-2000_E.html.-   10 D-EYE Portable Retinal Imaging System. D-EYE Srl. Cited Aug.    31, 2017. Available from: https://www.d-eyecare.com/en_US#vision.-   11 Pictor Plus Ophthalmic Camera. Volk Optical, Inc. Cited Dec.    2, 2017. Available from:    https://volk.com/index.php/volk-products/ophthalmic-cameras/volk-pictor-plus-digital-ophthalmic-imager.html.-   12 Visuscout 100 Handheld Fundus Camera. Carl Zeiss Meditec, Inc.    Cited Dec. 2, 2017. Available from:    https://www.zeiss.com/meditec/us/products/ophthalmology-optometry/essential-line-basic-diagnostics/iop-and-retina-screening/visuscout-100.html.-   13 The Horus Scope. Jedmed. Cited Dec. 2, 2017. Available from:    https://www.jedmed.com/products/portable-fundus-camera.-   14 Envisu C2300. Leica Microsystems. Cited Aug. 31, 2017. Available    from:    http://www.leica-microsystems.com/products/optical-coherence-tomography-oct/details/product/envisu-c-class/.-   15 iScan. Optovue, Inc. Cited Dec. 2, 2017. Available from:    http://www.optovue.com/products/iscan/.-   16 Vinekar A, Sivakumar M, Shetty R, Mahendradas P, Krishnan N,    Mallipatna A, et al. A novel technique using spectral-domain optical    coherence tomography (Spectralis, SD-OCT+HRA) to image supine    non-anaesthetized infants: utility demonstrated in aggressive    posterior retinopathy of prematurity. Eye (Lond). 2010;    24(2):379-82.-   17 Tao Y K, Ehlers J P, Toth C A, Izatt J A. Intraoperative spectral    domain optical coherence tomography for vitreoretinal surgery. Opt    Lett. 2010; 35(20):3315-7.-   18 Ehlers J P, Tao Y K, Farsiu S, Maldonado R, Izatt J A, Toth C A.    Integration of a spectral domain optical coherence tomography system    into a surgical microscope for intraoperative imaging. Invest    Ophthalmol Vis Sci. 2011; 52(6):3153-9.-   19 Lu C D, Kraus M F, Potsaid B, Liu J J, Choi W, Jayaraman V, et    al. Handheld ultrahigh speed swept source optical coherence    tomography instrument using a MEMS scanning mirror. Biomed Opt    Express. 2013; 5(1):293-311.-   20 Kim S, Crose M, Eldridge W J, Cox B, Brown W J, Wax A. Design and    implementation of a low-cost portable OCT system. Biomed Opt    Express. 2018; 9(3):1232-1243.

While the devices, systems, and methods of the present disclosure havebeen described in detail with reference to exemplary embodimentsthereof, it will be apparent to one skilled in the art that variouschanges can be made, and equivalents employed, without departing fromthe scope of the invention. The foregoing description of the exemplaryembodiments of the devices, methods, and systems has been presented forpurposes of illustration and description. It is not intended to beexhaustive or to limit the invention to the precise form disclosed, andmodifications and variations are possible in light of the aboveteachings or may be acquired from practice of the invention. Theembodiments were chosen and described in order to explain the principlesof the devices, systems, and methods and practical applications of thesame to enable one skilled in the art to utilize the disclosed devices,systems, and methods in various embodiments as are suited to theparticular use contemplated. It is intended that the scope of thepresent disclosure be defined by the claims appended hereto, and theirequivalents. The entirety of each of the aforementioned documents isincorporated by reference herein.

That which is claimed is:
 1. A system useful for FAF and OCT imageacquisition of a patient's eye, the system comprising: a broadband LEDas an FAF light source; a tunable laser as an OCT light source; acoupler; a first lightpath communicating visible light from thebroadband LED, the first lightpath including an excitation filter, thefirst lightpath communicating light from the excitation filter to thecoupler; a second lightpath communicating near infrared light from saidtunable laser to said coupler, wherein the coupler combines light fromsaid first and second lightpaths; a single-mode fiber receiving lightfrom said coupler; a splitter receiving light form said single-modefiber; third and fourth lightpaths receiving light from said splitter; areference arm in said third lightpath; and a headset sample arm in saidfourth lightpath.
 2. A system according to claim 1, wherein thebroadband LED has a 1060 nm center wavelength and the tunable laser hasa 100 kHz sweep rate.
 3. A system according to claim 1, wherein theexcitation filter operates at 535-585 nm.
 4. A system according to claim1, wherein said combining comprises combining at a 2×1 wavelengthdivision multiplexer coupler and into a single-mode fiber for sequentialFAF and OCT imaging.
 5. A system according to claim 1, wherein saidreference arm comprises a collimator, achromatic doublet lens, andstatic silver-coated reference mirror.
 6. A system according to claim 1,wherein said splitting and transmitting light is performed via athrough-port of a double-cladding fiber coupler.
 7. A process of FAF andOCT image acquisition of a patient's eye, the process comprising:generating light with a broadband LED and tunable laser, wherein visiblelight from the broadband LED first travels through a lipofuscinexcitation filter; combining light from said excitation filter with nearinfrared light from said tunable laser; splitting and transmitting lightfrom said combining step to a reference arm, and a headset sample armconfigured to be positioned in front of a patient's eye.
 8. A processaccording to claim 7, further comprising: simultaneously acquiring FAFand OCT images of said eye.
 9. A process according to claim 7, whereinthe broadband LED has a 1060 nm center wavelength and the tunable laserhas a 100 kHz sweep rate.
 10. A process according to claim 7, whereinthe excitation filter operates at 535-585 nm.
 11. A process according toclaim 7, wherein said combining comprises combining at a 2×1 wavelengthdivision multiplexer coupler and into a single-mode fiber for sequentialFAF and OCT imaging.
 12. A process according to claim 7, wherein saidreference arm comprises a collimator, achromatic doublet lens, andstatic silver-coated reference mirror.
 13. A process according to claim7, wherein said splitting and transmitting light is performed via athrough-port of a double-cladding fiber coupler.